This project built and trained a convolutional neural network in Keras from scratch to recognize facial expressions.
The data comprises of 48px by 48px grayscale data images. The objective is to classify each face based on the emotion shown in the facial expression into one of seven categories.
Use of OpenCV to automatically detect faces in images and draw bounding boxes around them. After training, saving, and exporting the CNN, it then served the trained model to a web interface with Flask, and performed real-time facial expression recognition on real-time video streams and image data.
To deploy this project run
python3 main.pyIf you have any feedback, please reach out to me at [email protected]